a star, robot uwzglednia koszt
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@ -91,14 +91,14 @@ class AI:
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for mine in self.current_map.mines:
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# dists.append(sqrt((self.saper.position_x-mine.position_x)**2 + (self.saper.position_y-mine.position_y)**2))
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dists.append(abs(self.saper.position_x - mine.position_x) + abs(self.saper.position_y - mine.position_y))
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print(dists)
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#print(dists)
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ind = dists.index(min(dists)) # choose nearest mine
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goal_state = [self.current_map.mines[ind].position_x, self.current_map.mines[ind].position_y]
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print(f'We go to {goal_state}')
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find_path = bfs.BFS(self.saper, self.window)
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tmp = find_path.graphsearch([], [], bfs.BFS.successor, goal_state)
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print(f'tmp = {tmp}')
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#print(f'tmp = {tmp}')
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if tmp is None:
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raise Exception("Error, path does not exist")
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else:
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@ -151,7 +151,7 @@ class BFS:
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position_at_beginning = [self.agent.position_x, self.agent.position_y, self.agent.rotation_degrees] # x, y, gdzie_patczy
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final_action_list = [] # lista co ma robic zeby dojechac do miny
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root = node.Node(None, None, position_at_beginning, 0) # parent, action, position, cost
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root = node.Node(None, None, position_at_beginning, 2) # parent, action, position, cost
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heapq.heappush(fringe, (0, root)) # add first node to fringe
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@ -162,6 +162,7 @@ class BFS:
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if len(fringe) == 0:
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return False
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# get node from fringe
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tmp_node = heapq.heappop(fringe) # tuple(priority, node)
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tmp_node_position = tmp_node[1].get_position() # x, y , gdzie patczy
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@ -184,14 +185,14 @@ class BFS:
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neighbours_list_of_our_node = self.successor(tmp_node_position) # lista możliwych akcij
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print(neighbours_list_of_our_node)
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for node_ in neighbours_list_of_our_node:
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# node_ is tuple(action, [x, y, gdzie_patczy], cost)
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notInFringe = True # false if node in fringe
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notInExplored = True # false if node in explored
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# if node_[1] is None:
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# continue
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p = manhattan(node_[1], goaltest) + node_[2]
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# wyznacza jaki jest priorytet nastempnika
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@ -199,7 +200,7 @@ class BFS:
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priority_in_fringe = 0
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counter = 0
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tmp_position_in_fringe = 0 # zero if node not in fringe
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index_of_node_in_fringe = 0 # zero if node not in fringe
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for fringeNode in fringe: # isc po wszystkich wezlach ktore juz sa w fringe
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# jesli nasz wezel juz jest w fringe
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@ -207,7 +208,7 @@ class BFS:
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notInFringe = False
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priority_in_fringe = fringeNode[0]
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# number of element in fringe
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tmp_position_in_fringe = counter
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index_of_node_in_fringe = counter
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counter = counter + 1
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@ -224,10 +225,10 @@ class BFS:
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# if node not in fringe
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elif notInFringe is False and (priority_in_fringe > p):
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x = node.Node(tmp_node, node_[0], node_[1], node_[2]) # parent, action, state_array, cost
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tmp = list(fringe[tmp_position_in_fringe])
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tmp = list(fringe[index_of_node_in_fringe])
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tmp[0] = p
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tmp[1] = x
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fringe[tmp_position_in_fringe] = tuple(tmp)
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fringe[index_of_node_in_fringe] = tuple(tmp)
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#self.window.draw_search([self.agent.position_x, self.agent.position_y], [node_[1][0], node_[1][1]],self.agent.current_map.tile_size, self.agent.current_map, self.agent)
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